Immediate Effect of Mental Imagery in Improving Soccer Passing and Control Skill among Male Collegiate-Level Players: A Pilot Study
Bibliographic record
Abstract
A BSTRACT Introduction: Mental imagery is used to re-create a sporting experience in the mind to enhance sporting performance. Passing and control skill in soccer, needs precision, accuracy and speed. Imagery has not been extensively used in the Indian setup till date for collegiate-level players, belonging to an open sport wherein the environment keeps changing. A combination of external and internal imagery is also less researched. Study Aim: Aim of the study was to see the immediate effect of mental imagery in enhancing soccer passing and control skill in male collegiate-level players. Materials and Methods: This was a single group experimental study which evaluated 16 male collegiate soccer players, aged 18–25 years, playing soccer for minimum 5 hours/week for at least one year, playing at inter-collegiate level and not having any recent injury, fracture, open wounds over the past 6 months. All the 16 participants were tested for their passing and control skills using the Loughborough soccer passing test (LSPT), post which they underwent mental imagery (MI) intervention, following which all were re-assessed using LSPT. Results: The result of the study showed that there was a significant improvement ( P < 0.05) in the LSPT score measured pre and post imagery. Conclusion: Imagery hence proves to be an important tool for maintaining focus on skillsets, strength and power post-injury and surgery, during detraining and return to sport. Mental imagery can be a beneficial tool in improving skill-specific training, strength and power training post-injury and surgery, during detraining and return to sport in collegiate-level athletes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".